Let me tell you a story about how, in reality, institutional money flows into the financial infrastructure of today. It follows compliance architecture, the credibility of developers, settlement success, and a robust lending model. It doesn’t form a line in front of platforms with the most Twitter activity or aggressive roadmaps and non-stop conferencing with investors. The loudest conversations simply don’t clear the path for institutional involvement. They make quiet, cold, calculated decisions by analyzing long and hard, […]

Ver mais

arXiv:2602.21416v1 Announce Type: new Abstract: We introduce the task of SVG extraction, which consists in translating specific visual inputs from an image into scalable vector graphics. Existing multimodal models achieve strong results when generating SVGs from clean renderings or textual descriptions, but they fall short in real-world scenarios where natural images introduce noise, clutter, and domain shifts. A central challenge in this direction is the lack of suitable benchmarks. To address this need, we introduce the WildSVG Benchmark, […]

Ver mais

arXiv:2602.02554v1 Announce Type: new Abstract: Training LLMs for code-related tasks typically depends on high-quality code-documentation pairs, which are costly to curate and often scarce for niche programming languages. We introduce BatCoder, a self-supervised reinforcement learning framework designed to jointly optimize code generation and documentation production. BatCoder employs a back-translation strategy: a documentation is first generated from code, and then the generated documentation is used to reconstruct the original code. The semantic similarity between the original and reconstructed code […]

Ver mais

arXiv:2603.03475v1 Announce Type: new Abstract: Mathematical reasoning models are widely deployed in education, automated tutoring, and decision support systems despite exhibiting fundamental computational instabilities. We demonstrate that state-of-the-art models (Qwen2.5-Math-7B) achieve 61% accuracy through a mixture of reliable and unreliable reasoning pathways: 18.4% of correct predictions employ stable, faithful reasoning while 81.6% emerge through computationally inconsistent pathways. Additionally, 8.8% of all predictions are silent failures — confident yet incorrect outputs. Through comprehensive analysis using novel faithfulness metrics, we […]

Ver mais

Scaling from $50 to $10,000 a day should feel like pressing a magic button. It should create a system that keeps running without breaking. After reviewing over 100 ad accounts, I have learned that most media buyers don’t fail because their ads are bad. But they fail because they don’t have a clear map for the tricky points in scaling. So, if you feel stuck, here’s the exact step-by-step plan I use to reach $10k/day safely. The Deadliest […]

Ver mais

arXiv:2602.06179v1 Announce Type: new Abstract: Pelvic diseases in women of reproductive age represent a major global health burden, with diagnosis frequently delayed due to high anatomical variability, complicating MRI interpretation. Existing AI approaches are largely disease-specific and lack real-time compatibility, limiting generalizability and clinical integration. To address these challenges, we establish a benchmark framework for disease- and parameter-agnostic, real-time-compatible unsupervised anomaly detection in pelvic MRI. The method uses a residual variational autoencoder trained exclusively on healthy sagittal T2-weighted […]

Ver mais

arXiv:2601.10796v1 Announce Type: new Abstract: Effective physical human-robot interaction requires systems that are not only adaptable to user preferences but also transparent about their actions. This paper introduces BRIDGE, a system for bidirectional human-robot communication in physical assistance. Our method allows users to modify a robot’s planned trajectory — position, velocity, and force — in real time using natural language. We utilize a large language model (LLM) to interpret any trajectory modifications implied by user commands in the […]

Ver mais